[R] for loop help

[Adaikalavan Ramasamy]

Try changing

    outliers <- subset(pre.outliers, gtvalue4FWHM >= 0.00)

to

    w <- which( gtvalue4FWHM >= 0.00 )
    outliers( length(w) > 0, pre.outliers[ w, ],  NA )


Other comments:

1. Make sure you detach(data_gcs) at the end of the loops


2. scale() works on columns by default, so try
     current.roi.plus.z <- data.frame(current.roi,
                                   scale(current.roi[, c(15,18,21,24)]) )


3. For simple statements, you can use ifelse() syntax. Also see all(). 
Using these two functions, you can try

  testextrem <- function(x) ifelse( all(abs(x[ 1:4 ]) < c(2.5)), 1, 0)


4. Try to minimise the use of attach() in loops.

5. You might be interested in learning more about apply(), tapply(), 
split() etc.


If this does not help, then please resend a simplified version of the 
codes, preferably with a simple toy example to illustrate.

Regards, Adai



Anthony Steven Dick wrote:
> Hello-
> 
> I have a script which steps through a series of subjects, and for the 
> subjects I remove outlying values. After removing these outliers, I 
> specify a cutoff, keeping only values over a certain value (e.g., 1.96). 
> I want to populate a matrix with a statistic of the values that make the 
> cutoff (for example, the mean). However, in some subjects, after 
> outliers and the cutoff are specified, there are no data that meet the 
> criteria (I get <0 rows> (or 0-length row.names)). Here the script dies.
> 
> The solution I think is to specify a break so that the matrix will be 
> populated with a value (such as NA) and it will move on to the next 
> subject in the loop. However, I haven't been able to figure this out. If 
> anyone has any suggestions I would very much appreciate them. I have 
> paster part of the script below up to the point where it dies.
> 
> Thanks.
> 
> for (ss in levels(ss.list)) {
>         print(ss)
>         ss.count = ss.count + 1  
>         query.string <- paste("SELECT * FROM ",ss,";",sep="")
>         #print(query.string)
>         data_gcs <- dbGetQuery(con, query.string)
>         attach(data_gcs)
>         names(data_gcs)
>         mat_row = 0
>             for(i in levels(roi.list)){
>             print (i)
>             current.roi <- data_gcs[data_gcs$ROI==i,]
>             current.roi.plus.z <- data.frame(current.roi, 
> scale(current.roi[,15]), scale(current.roi[,18]), 
> scale(current.roi[,21]), scale(current.roi[,24]))
>             testextrem <- function(x) {if ((abs(x[1]) < 2.5) & 
> (abs(x[2]) < 2.5) & (abs(x[3]) < 2.5) & (abs(x[4]) < 2.5)) return(1) 
> else return(0)}
>             filtervector <- apply(as.vector(current.roi.plus.z[,c(27, 
> 28, 29, 30)]), 1, FUN=testextrem)
>             current.roi.plus.z.filter <- data.frame(current.roi.plus.z, 
> filtervector)
>             final.roi.df <- 
> current.roi.plus.z.filter[which(current.roi.plus.z.filter$filtervector==1),]
>             #print (final.roi.df)
>             kicked.out<-(length(filtervector) - 
> sum(filtervector))/length(filtervector)
>             print(kicked.out)
>             matrix.col = matrix.col + 1
>             attach(final.roi.df)
>             names(final.roi.df)
>             print(matrix.col)
>             #set cutoff for FDR. per voxel p values (of Z dist) .05 = 
> 1.96, .01 = 2.575, .001 = 3.277, .005 = 3.479 BE SURE TO CHANGE THE 
> VARIABLE EACH TIME YOU CHANGE CONDITION
>                pre.outliers<-subset(final.roi.df, gFDR4FWHM >= 1.96)
>                detach(final.roi.df)
>                attach(pre.outliers)
>                outliers<-subset(pre.outliers, gtvalue4FWHM >= 0.00)
> ...and the script dies here because there are no data in "outliers".
>